On Adaptive Attacks to Adversarial Example Defenses

19 February 2020

Wieland Brendel

Papers citing "On Adaptive Attacks to Adversarial Example Defenses"

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Title
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? Vikash Sehwag Saeed Mahloujifar Tinashe Handina Sihui Dai Chong Xiang M. Chiang Prateek Mittal OOD 29 126 0 19 Apr 2021
FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems Liang Tong Zhengzhang Chen Jingchao Ni Wei Cheng Dongjin Song Haifeng Chen Yevgeniy Vorobeychik CVBM AAML 19 19 0 08 Apr 2021
The art of defense: letting networks fool the attacker Jinlai Zhang Lyvjie Chen Binbin Liu Bojun Ouyang Jihong Zhu Minchi Kuang Houqing Wang Yanmei Meng AAML 3DPC 9 15 0 07 Apr 2021
TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness Zhuolin Yang Linyi Li Xiaojun Xu Shiliang Zuo Qiang Chen Benjamin I. P. Rubinstein Pan Zhou Ce Zhang Bo-wen Li AAML 16 53 0 01 Apr 2021
On the Robustness of Vision Transformers to Adversarial Examples Kaleel Mahmood Rigel Mahmood Marten van Dijk ViT 11 217 0 31 Mar 2021
Robustness Certification for Point Cloud Models Tobias Lorenz Anian Ruoss Mislav Balunović Gagandeep Singh Martin Vechev 3DPC 13 26 0 30 Mar 2021
Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries Kun-Peng Ning Lue Tao Songcan Chen Sheng-Jun Huang AAML OOD 11 14 0 27 Mar 2021
Combating Adversaries with Anti-Adversaries Motasem Alfarra Juan C. Pérez Ali K. Thabet Adel Bibi Philip H. S. Torr Bernard Ghanem AAML 6 26 0 26 Mar 2021
Adversarial Attacks are Reversible with Natural Supervision Chengzhi Mao Mia Chiquer Hao Wang Junfeng Yang Carl Vondrick BDL AAML 6 54 0 26 Mar 2021
Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales Yifan Sun Yuke Zhu Yuhan Zhang Pengkun Zheng Xi Qiu Chi Zhang Yichen Wei 26 17 0 22 Mar 2021
Adversarially Optimized Mixup for Robust Classification Jason Bunk Srinjoy Chattopadhyay B. S. Manjunath S. Chandrasekaran AAML 11 8 0 22 Mar 2021
Bio-inspired Robustness: A Review Harshitha Machiraju Oh-hyeon Choung P. Frossard Michael H. Herzog AAML 19 1 0 16 Mar 2021
Generating Unrestricted Adversarial Examples via Three Parameters Hanieh Naderi Leili Goli S. Kasaei 22 8 0 13 Mar 2021
Attack as Defense: Characterizing Adversarial Examples using Robustness Zhe Zhao Guangke Chen Jingyi Wang Yiwei Yang Fu Song Jun Sun AAML 17 31 0 13 Mar 2021
Improving Adversarial Robustness via Channel-wise Activation Suppressing Yang Bai Yuyuan Zeng Yong Jiang Shutao Xia Xingjun Ma Yisen Wang AAML 27 129 0 11 Mar 2021
Practical Relative Order Attack in Deep Ranking Mo Zhou Le Wang Zhenxing Niu Qilin Zhang Yinghui Xu N. Zheng G. Hua 11 18 0 09 Mar 2021
WaveGuard: Understanding and Mitigating Audio Adversarial Examples Shehzeen Samarah Hussain Paarth Neekhara Shlomo Dubnov Julian McAuley F. Koushanfar AAML 18 71 0 04 Mar 2021
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples Washington Garcia Pin-Yu Chen S. Jha Scott Clouse Kevin R. B. Butler AAML 17 0 0 04 Mar 2021
SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain P. Harder Franz-Josef Pfreundt M. Keuper J. Keuper AAML 8 47 0 04 Mar 2021
Federated Learning without Revealing the Decision Boundaries Roozbeh Yousefzadeh FedML 6 0 0 01 Mar 2021
Model-Agnostic Defense for Lane Detection against Adversarial Attack Henry Xu An Ju David A. Wagner AAML 8 6 0 01 Mar 2021
What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning Jonas Geiping Liam H. Fowl Gowthami Somepalli Micah Goldblum Michael Moeller Tom Goldstein TDI AAML SILM 11 40 0 26 Feb 2021
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints Maura Pintor Fabio Roli Wieland Brendel Battista Biggio AAML 36 70 0 25 Feb 2021
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 11 57 0 25 Feb 2021
Robust SleepNets Yigit Can Alparslan Edward J. Kim AAML 16 1 0 24 Feb 2021
Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis Leo Schwinn A. Nguyen René Raab Leon Bungert Daniel Tenbrinck Dario Zanca Martin Burger Bjoern M. Eskofier AAML 13 13 0 24 Feb 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses Chengyuan Yao Pavol Bielik Petar Tsankov Martin Vechev AAML 11 24 0 23 Feb 2021
On the robustness of randomized classifiers to adversarial examples Rafael Pinot Laurent Meunier Florian Yger Cédric Gouy-Pailler Y. Chevaleyre Jamal Atif AAML 21 14 0 22 Feb 2021
Bridging the Gap Between Adversarial Robustness and Optimization Bias Fartash Faghri Sven Gowal C. N. Vasconcelos David J. Fleet Fabian Pedregosa Nicolas Le Roux AAML 184 7 0 17 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 17 45 0 15 Feb 2021
Data Quality Matters For Adversarial Training: An Empirical Study Chengyu Dong Liyuan Liu Jingbo Shang AAML 11 10 0 15 Feb 2021
Dompteur: Taming Audio Adversarial Examples Thorsten Eisenhofer Lea Schonherr Joel Frank Lars Speckemeier D. Kolossa Thorsten Holz AAML 18 24 0 10 Feb 2021
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons Bohang Zhang Tianle Cai Zhou Lu Di He Liwei Wang OOD 27 49 0 10 Feb 2021
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection Hanshu Yan Jingfeng Zhang Gang Niu Jiashi Feng Vincent Y. F. Tan Masashi Sugiyama AAML 8 41 0 10 Feb 2021
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models Sahar Abdelnabi Mario Fritz AAML 8 7 0 09 Feb 2021
Target Training Does Adversarial Training Without Adversarial Samples Blerta Lindqvist AAML 8 0 0 09 Feb 2021
Noise Optimization for Artificial Neural Networks Li Xiao Zeliang Zhang Yijie Peng 31 13 0 06 Feb 2021
Optimal Transport as a Defense Against Adversarial Attacks Quentin Bouniot Romaric Audigier Angélique Loesch AAML OOD 6 9 0 05 Feb 2021
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks Chong Xiang Prateek Mittal AAML 21 52 0 05 Feb 2021
Adversarial Robustness Study of Convolutional Neural Network for Lumbar Disk Shape Reconstruction from MR images Jiasong Chen Linchen Qian Timur Urakov Weiyong Gu Liang Liang AAML OOD 6 12 0 04 Feb 2021
IWA: Integrated Gradient based White-box Attacks for Fooling Deep Neural Networks Yixiang Wang Jiqiang Liu Xiaolin Chang J. Misic Vojislav B. Mišić AAML 28 12 0 03 Feb 2021
On managing vulnerabilities in AI/ML systems Jonathan M. Spring April Galyardt A. Householder Nathan M. VanHoudnos 10 17 0 22 Jan 2021
Understanding the Error in Evaluating Adversarial Robustness Pengfei Xia Ziqiang Li Hongjing Niu Bin Li AAML ELM 27 5 0 07 Jan 2021
Adversarial Robustness by Design through Analog Computing and Synthetic Gradients Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krzakala AAML 44 13 0 06 Jan 2021
Barking up the right tree: an approach to search over molecule synthesis DAGs John Bradshaw Brooks Paige Matt J. Kusner Marwin H. S. Segler José Miguel Hernández-Lobato 32 56 0 21 Dec 2020
On Success and Simplicity: A Second Look at Transferable Targeted Attacks Zhengyu Zhao Zhuoran Liu Martha Larson AAML 17 120 0 21 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers Jonathan W. Helland Nathan M. VanHoudnos AAML 14 4 0 18 Dec 2020
A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks Qingsong Yao Zecheng He Yi Lin Kai Ma Yefeng Zheng S. Kevin Zhou AAML MedIm 20 16 0 17 Dec 2020
FoggySight: A Scheme for Facial Lookup Privacy Ivan Evtimov Pascal Sturmfels Tadayoshi Kohno PICV FedML 11 24 0 15 Dec 2020
Data-Dependent Randomized Smoothing Motasem Alfarra Adel Bibi Philip H. S. Torr Bernard Ghanem UQCV 16 34 0 08 Dec 2020